Data Scientist

Kiya.ai; Chennai District; On-site; INR 1,200,000 - 1,500,000; Full time

Job summary

A leading AI company in Chennai seeks a Data Scientist with 5 to 8 years of experience. Your role involves designing and maintaining RAG architecture, implementing vector embeddings for semantic search, and developing AI solutions to meet business needs. The ideal candidate should have strong knowledge of Python, R, and machine learning algorithms. Excellent communication skills and the ability to analyze large datasets are essential. Interested candidates can send profiles via email to the HR contact provided.

Qualifications

• 5 to 8 years of experience in data science or related field.
• Excellent communication and listening skills.

Responsibilities

• Design and maintain RAG connecting CRM to LLM for AI responses.
• Implement and maintain vector embeddings for semantic search.
• Design and deploy MCP for real-time data retrieval.
• Utilize LLMs for generating user-friendly responses.
• Lead code reviews and ensure coding standards adherence.
• Collect and analyze large datasets for insights.

Skills

Python

R

SQL

Machine learning algorithms

PyTorch or TensorFlow

RAG / Architecture

CRM Schema

Job description

Position : Data Scientist

Experience : 5 to 8 Years

Notice period; Immediate to 15 Days (Not more than)

Location : Chennai

Type Of Interview : F2F Interview (Final Discussion)

Responsibilities

1. RAG Architecture & Pipeline Design
   • Design and maintain RAG that connects CRM to LLM to provide grounded, fact based AI responses.
2. Vector Search & NLP
   • Implement and maintain vector embeddings for entities to enable semantic search and integration with LLM for generative AI features.
3. MCP Server Development
   • Design and deploy MCP to bridge LLM with existing Data sources for real-time Retrieval.
4. Generative AI Integration
   • Utilize LLMs to synthesize retrieved data into accurate, user friendly natural language responses.
5. Performance Optimization
   • Evaluate and optimize the end-to-end latency of search and generation.
6. Data Analysis
   • Collect, analyze, and interpret large datasets to identify trends, patterns, and insights that can inform business decisions.
7. Technical Leadership
   • Lead code reviews, ensuring adherence to coding standards, best practices, and quality requirements.
   • Act as a technical point of contact for complex database issues, offering solutions and recommendations to resolve them.
8. Project Coordination and Stakeholder Collaboration
   • Collaborate with project managers, business analysts, and stakeholders to understand business requirements and translate them into technical solutions.
9. Quality Assurance and testing
   • Collaborate with QA teams to validate data quality, ensure accuracy, and troubleshoot issues identified during testing.
10. Continuous Improvement
    • Stay up-to on the latest tools, techniques, and best practices.
    • Identify opportunities for process improvements, optimizations, and automation.
11. Documentation and Standards
    • Ensure adherence to data governance and regulatory requirements, including security and compliance standards.

Contributing Responsibilities

• Design, develop, implement and maintain AI/LLM products to solve specific business use cases.
• Implement and maintain vector embeddings for entities to enable semantic search and integration with LLM for generative AI features.
• Design and deploy MCP to bridge LLM with existing Data sources for real-time Retrieval.
• Design and maintain RAG that connects CRM to LLM to provide grounded, fact based AI responses.
• Explore and understand the CRM data, including customer demographics, behavior, and transactional data.
• Develop and train predictive models using various machine learning algorithms and techniques.
• Deploy models in production environments, such as CRM systems.
• Monitor model performance, identify areas for improvement, and retrain models as necessary.
• Generate insights and recommendations based on data analysis and modeling results.
• Communicate insights and results to stakeholders, including business leaders.
• Identify opportunities to improve CRM data quality, processes, and systems.
• Collaborate with project managers, business analysts, and stakeholders to understand business requirements and translate them into technical solutions.
• Stay current with industry trends, new technologies, and emerging methodologies in data science and CRM.
• Excellent Communication and Listening Skills, attention to details is must.

Technical & Behavioral Competencies

• Python, R, SQL
• Machine learning algorithms
• PyTorch or TensorFlow
• RAG / Architecture
• CRM Schema

If any one interested can share the profiles to "[e-mail]"

Regards,

Kalidasan Ramasamy

Human Resource
[e-mail]
www.kiya.ai